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001 978-981-10-1046-0
003 DE-He213
005 20200421112228.0
007 cr nn 008mamaa
008 160427s2016 si | s |||| 0|eng d
020 _a9789811010460
_9978-981-10-1046-0
024 7 _a10.1007/978-981-10-1046-0
_2doi
050 4 _aTK5102.9
050 4 _aTA1637-1638
050 4 _aTK7882.S65
072 7 _aTTBM
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aCOM073000
_2bisacsh
082 0 4 _a621.382
_223
100 1 _aBenesty, Jacob.
_eauthor.
245 1 0 _aFundamentals of Differential Beamforming
_h[electronic resource] /
_cby Jacob Benesty, Jingdong Chen, Chao Pan.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2016.
300 _aVIII, 122 p. 79 illus., 77 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
505 0 _aIntroduction -- Problem Formulation -- Some Background -- Performance Measures Revisited -- Conventional Optimization -- Beampattern Design -- Joint Optimization.
520 _aThis book provides a systematic study of the fundamental theory and methods of beamforming with differential microphone arrays (DMAs), or differential beamforming in short. It begins with a brief overview of differential beamforming and some popularly used DMA beampatterns such as the dipole, cardioid, hypercardioid, and supercardioid, before providing essential background knowledge on orthogonal functions and orthogonal polynomials, which form the basis of differential beamforming. From a physical perspective, a DMA of a given order is defined as an array that measures the differential acoustic pressure field of that order; such an array has a beampattern in the form of a polynomial whose degree is equal to the DMA order. Therefore, the fundamental and core problem of differential beamforming boils down to the design of beampatterns with orthogonal polynomials. But certain constraints also have to be considered so that the resulting beamformer does not seriously amplify the sensors' self noise and the mismatches among sensors. Accordingly, the book subsequently revisits several performance criteria, which can be used to evaluate the performance of the derived differential beamformers. Next, differential beamforming is placed in a framework of optimization and linear system solving, and it is shown how different beampatterns can be designed with the help of this optimization framework. The book then presents several approaches to the design of differential beamformers with the maximum DMA order, with the control of the white noise gain, and with the control of both the frequency invariance of the beampattern and the white noise gain. Lastly, it elucidates a joint optimization method that can be used to derive differential beamformers that not only deliver nearly frequency-invariant beampatterns, but are also robust to sensors' self noise.
650 0 _aEngineering.
650 1 4 _aEngineering.
650 2 4 _aSignal, Image and Speech Processing.
700 1 _aChen, Jingdong.
_eauthor.
700 1 _aPan, Chao.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789811010453
830 0 _aSpringerBriefs in Electrical and Computer Engineering,
_x2191-8112
856 4 0 _uhttp://dx.doi.org/10.1007/978-981-10-1046-0
912 _aZDB-2-ENG
942 _cEBK
999 _c57786
_d57786